Algorithms for Computing Self-Consistent and Maximum Likelihood Estimators with Doubly Censored Data
The paper investigates the structure of the self-consistent estimators (SCE) and the nonparametric maximum likelihood estimator (NPMLE) for doubly censored data. An explicit sufficient and necessary ...
Uniform a.s. consistency is proven for a class of kernel estimators of multivariate density functions in the independence case and under a mixing condition. Furthermore the Chernoff-estimator of the ...
We use influence functions as a basic tool to study unconditional nonparametric and parametric expected shortfall (ES) estimators with regard to returns data influence, standard errors and coherence.
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